The General Data Protection Regulation (GDPR) recently got approved. Are you and your organization ready to explain your models?

Jo-Fai Chow from H2O will lead us in a journey through the construction and interpretation of Machine Learning models, in an hand-on experience open to everybody (previous knowledge of ML is not required).

We will discover the use of two R packages, h2o & LIME, for automatic and interpretable machine learning. We will learn how to build regression and classification models quickly with H2O's AutoML. Then we will be guided to explain the model outcomes with a framework called Local Interpretable Model-Agnostic Explanations (LIME).

The workshop is free, but it is open to max 48 participants. Not much, are they? So make sure to be fast.

When you're sure you can be there, register on the Eventbrite event. If you change your mind, please unsubscribe from Eventbrite! This way you'll leave space for others.

Also keep your eye on the emails, because short before the workshop we'll ask you to confirm your participation (confirmation is mandatory to get your seat!!) and we'll give you instructions for installing all tools required, in order to be fully ready for the workshop.

The speaker will be Jo-Fai (or Joe) Chow, who works at H2O.ai as a a data science evangelist/community manager. Before joining H2O, he was in the business intelligence team at Virgin Media in UK where he developed data products to enable quick and smart business decisions. He also worked remotely for Domino Data Lab in the US as a data science evangelist promoting products via blogging and giving talks at meetups. He also holds an MSc in Environmental Management and a BEng in Civil Engineering.

H2O is open-source software for big-data analysis. It's used for exploring and analyzing datasets held in cloud computing systems and in the Apache Hadoop Distributed File System as well as in the conventional operating-systems Linux, macOS, and Microsoft Windows. The software is written in Java, Python, and R, and it's compatible with most browsers. The aim of H2O.ai (H2O's developers) is to develop an analytical interface for cloud computing and to provide all users with tools for data analysis. If you want to discover more about H2O, Machine Learning applications and business usecases, you can follow the livestream from the H2O World NYC on June 7th: https://h2oworld.h2o.ai/newyork/

The LIME is about explaining what machine learning classifiers (or models) are doing. LIME (short for local interpretable model-agnostic explanations) it's useful for interpretation of black-box classifiers with two or more classes, at an individual level